Jaydip Sen1, Nitish Mondal. 1. Department of Anthropology, University of North Bengal, India. jaydipsen@rediffmail.com
Abstract
BACKGROUND: The present cross-sectional study evaluates the utility of the Composite Index of Anthropometric Failure (CIAF) over conventional nutritional indices for nutritional assessment. It also assesses the impact of various socio-economic and demographic factors on the CIAF. SUBJECTS AND METHODS: Height, weight, age, socio-economic and demographic data were recorded from 3444 children (1682 boys; 1762 girls) aged 1-12 years and residing in Darjeeling district, West Bengal, India. The conventional anthropometric indices and CIAF were compared with the NCHS reference data to assess prevalence of under-nutrition. A multinomial logistic regression was used to assess the impact of different socio-economic and demographic variables on the CIAF. RESULTS: Prevalence of under-nutrition was observed to be 21.5% (wasting), 43.3% (stunting) and 52.0% (underweight). This increased to 63.6% using the CIAF. The multinomial logistic regression odds showed that children suffering from double and multiple failures were significantly associated with the socio-economic and demographic variables. CONCLUSION: The CIAF provides more precision in identifying the nutritionally vulnerable segment of the population. The disaggregation of CIAF has an adequate potential to enhance the efficacy of a nutritional intervention programme by identifying double or multiple failures.
BACKGROUND: The present cross-sectional study evaluates the utility of the Composite Index of Anthropometric Failure (CIAF) over conventional nutritional indices for nutritional assessment. It also assesses the impact of various socio-economic and demographic factors on the CIAF. SUBJECTS AND METHODS: Height, weight, age, socio-economic and demographic data were recorded from 3444 children (1682 boys; 1762 girls) aged 1-12 years and residing in Darjeeling district, West Bengal, India. The conventional anthropometric indices and CIAF were compared with the NCHS reference data to assess prevalence of under-nutrition. A multinomial logistic regression was used to assess the impact of different socio-economic and demographic variables on the CIAF. RESULTS: Prevalence of under-nutrition was observed to be 21.5% (wasting), 43.3% (stunting) and 52.0% (underweight). This increased to 63.6% using the CIAF. The multinomial logistic regression odds showed that children suffering from double and multiple failures were significantly associated with the socio-economic and demographic variables. CONCLUSION: The CIAF provides more precision in identifying the nutritionally vulnerable segment of the population. The disaggregation of CIAF has an adequate potential to enhance the efficacy of a nutritional intervention programme by identifying double or multiple failures.